Introduction to Data Science (2023)
2h 1mBeginner2023-07-31
Authors
Lavanya Vijayan
Coding instructor who is passionate about STEM education and diversity
Madecraft
Full-Service Learning Content Company
Course details
The world of data science is reshaping every business, regardless of industry, location, or role. And there’s never been a better time to get up to speed and learn the basics of this booming field. In this course, designed specifically for beginners, explore the world of data science, its opportunities and innovations, and the fundamental skills required for success.
Join Python trainer and data science expert Lavanya Vijayan as she shares what data science is and how it differs from other common data-related careers. Discover some of the most important tools used in the trade to develop your understanding of data libraries and data manipulation. Along the way, get an introduction to exploratory data analysis, data cleaning, data visualization, sampling, testing, estimating, and more. By the end of this course, you’ll know how to use inference and statistical analysis to make more reliable predictions for your business.
Join Python trainer and data science expert Lavanya Vijayan as she shares what data science is and how it differs from other common data-related careers. Discover some of the most important tools used in the trade to develop your understanding of data libraries and data manipulation. Along the way, get an introduction to exploratory data analysis, data cleaning, data visualization, sampling, testing, estimating, and more. By the end of this course, you’ll know how to use inference and statistical analysis to make more reliable predictions for your business.
Skills covered
Data Science FoundationsData ScienceOne-Off
Concepts
Introduction
- Beginning your data science exploration
Defining Data Science
- Demystifying data science
- The value of data science
- Defining the data science life cycle
Starting with Data Design
- Reducing bias with probability sampling
- Using non-probability sampling
Utilizing Computational Tools
- Comparing Python and R
- Setting up your Jupyter environment
Structuring Your Tabular Data
- Defining tabular data
- Reading tabular data
- Interpreting tabular data
- Gathering insights
- Answering specific questions
Using Exploratory Data Analysis
- Defining exploratory data analysis
- Recognizing statistical data types
- Distinguishing properties of data
Cleaning Your Data
- Explaining data cleaning
- Questions to guide data cleaning
Using Data Visualization
- Demystifying data visualization
- Visualizing your qualitative data
- Visualizing your quantitative data
Using Inference and Statistical Analysis
- Defining inference
- Designing a hypothesis test
- Creating a permutation
- Conducting a permutation test
- Bootstrapping a confidence interval
Using Prediction in Data Science
- Defining prediction for data science
- Navigating classification
- Recognizing the k-NN algorithm
- Implementing k-Nearest Neighbors
- Navigating regression
- Checking assumptions of regression
- Implementing linear regression
Conclusion
- Next steps